scholarly journals EngraveChain: A Blockchain-Based Tamper-Proof Distributed Log System

2021 ◽  
Vol 13 (6) ◽  
pp. 143
Author(s):  
Louis Shekhtman ◽  
Erez Waisbard
Keyword(s):  
Medical Records ◽  
Large Scale ◽  
Distributed Storage ◽  
Security And Privacy ◽  
Medical Systems ◽  
Financial Systems ◽  
Record System ◽  
Scalability Analysis ◽  
Multiple Copies ◽  
System Access

A reliable log system is a prerequisite for many applications. Financial systems need to have transactions logged in a precise manner, medical systems rely on having trusted medical records and security logs record system access requests in order to trace malicious attempts. Keeping multiple copies helps to achieve availability and reliability against such hackers. Unfortunately, maintaining redundant copies in a distributed manner in a byzantine setting has always been a challenging task, however it has recently become simpler given advances in blockchain technologies. In this work, we present a tamper-resistant log system through the use of a blockchain. We leverage the immutable write action and distributed storage provided by the blockchain as a basis to develop a secure log system, but we also add a privacy preserving layer that is essential for many applications. We detail the security and privacy aspects of our solution, as well as how they relate to performance needs in relevant settings. Finally, we implement our system over Hyperledger Fabric and demonstrate the system’s value for several use cases. In addition, we provide a scalability analysis for applying our solution in a large-scale system.

scholarly journals HealthyBlock: Blockchain-Based IT Architecture for Electronic Medical Records Resilient to Connectivity Failures

2020 ◽  
Vol 17 (19) ◽  
pp. 7132
Author(s):  
Omar Gutiérrez ◽  
Giordy Romero ◽  
Luis Pérez ◽  
Augusto Salazar ◽  
Marina Charris ◽  
...  
Keyword(s):  
Medical Record ◽  
Electronic Medical Record ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Medical Information ◽  
High Efficiency ◽  
Electronic Medical Record System ◽  
Security And Privacy ◽  
Record System ◽  
Treatment And Prevention

The current information systems for the registration and control of electronic medical records (EMR) present a series of problems in terms of the fragmentation, security, and privacy of medical information, since each health institution, laboratory, doctor, etc. has its own database and manages its own information, without the intervention of patients. This situation does not favor effective treatment and prevention of diseases for the population, due to potential information loss, misinformation, or data leaks related to a patient, which in turn may imply a direct risk for the individual and high public health costs for governments. One of the proposed solutions to this problem has been the creation of electronic medical record (EMR) systems using blockchain networks; however, most of them do not take into account the occurrence of connectivity failures, such as those found in various developing countries, which can lead to failures in the integrity of the system data. To address these problems, HealthyBlock is presented in this paper as an architecture based on blockchain networks, which proposes a unified electronic medical record system that considers different clinical providers, with resilience in data integrity during connectivity failure and with usability, security, and privacy characteristics. On the basis of the HealthyBlock architecture, a prototype was implemented for the care of patients in a network of hospitals. The results of the evaluation showed high efficiency in keeping the EMRs of patients unified, updated, and secure, regardless of the network clinical provider they consult.

scholarly journals Medical records-based chronic kidney disease phenotype for clinical care and “big data” observational and genetic studies

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Ning Shang ◽  
Atlas Khan ◽  
Fernanda Polubriaginof ◽  
Francesca Zanoni ◽  
Karla Mehl ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Medical Records ◽  
Large Scale ◽  
Association Studies ◽  
Clinical Care ◽  
Medical Systems ◽  
Genetic Studies ◽  
Genome Wide ◽  
Independent Case

AbstractChronic Kidney Disease (CKD) represents a slowly progressive disorder that is typically silent until late stages, but early intervention can significantly delay its progression. We designed a portable and scalable electronic CKD phenotype to facilitate early disease recognition and empower large-scale observational and genetic studies of kidney traits. The algorithm uses a combination of rule-based and machine-learning methods to automatically place patients on the staging grid of albuminuria by glomerular filtration rate (“A-by-G” grid). We manually validated the algorithm by 451 chart reviews across three medical systems, demonstrating overall positive predictive value of 95% for CKD cases and 97% for healthy controls. Independent case-control validation using 2350 patient records demonstrated diagnostic specificity of 97% and sensitivity of 87%. Application of the phenotype to 1.3 million patients demonstrated that over 80% of CKD cases are undetected using ICD codes alone. We also demonstrated several large-scale applications of the phenotype, including identifying stage-specific kidney disease comorbidities, in silico estimation of kidney trait heritability in thousands of pedigrees reconstructed from medical records, and biobank-based multicenter genome-wide and phenome-wide association studies.

scholarly journals ‘CTRL’: an online, Dynamic Consent and participant engagement platform working towards solving the complexities of consent in genomic research

2021 ◽  
Author(s):  
Matilda A. Haas ◽  
Harriet Teare ◽  
Megan Prictor ◽  
Gabi Ceregra ◽  
Miranda E. Vidgen ◽  
...  
Keyword(s):  
Large Scale ◽  
Genomic Medicine ◽  
International Standards ◽  
Security And Privacy ◽  
Genomic Research ◽  
Return Of Results ◽  
Future Research ◽  
Design And Development ◽  
Participant Engagement ◽  
Dynamic Consent

AbstractThe complexities of the informed consent process for participating in research in genomic medicine are well-documented. Inspired by the potential for Dynamic Consent to increase participant choice and autonomy in decision-making, as well as the opportunities for ongoing participant engagement it affords, we wanted to trial Dynamic Consent and to do so developed our own web-based application (web app) called CTRL (control). This paper documents the design and development of CTRL, for use in the Australian Genomics study: a health services research project building evidence to inform the integration of genomic medicine into mainstream healthcare. Australian Genomics brought together a multi-disciplinary team to develop CTRL. The design and development process considered user experience; security and privacy; the application of international standards in data sharing; IT, operational and ethical issues. The CTRL tool is now being offered to participants in the study, who can use CTRL to keep personal and contact details up to date; make consent choices (including indicate preferences for return of results and future research use of biological samples, genomic and health data); follow their progress through the study; complete surveys, contact the researchers and access study news and information. While there are remaining challenges to implementing Dynamic Consent in genomic research, this study demonstrates the feasibility of building such a tool, and its ongoing use will provide evidence about the value of Dynamic Consent in large-scale genomic research programs.

scholarly journals Providing large-scale disk storage at CERN

2019 ◽  
Vol 214 ◽  
pp. 04033
Author(s):  
Hervé Rousseau ◽  
Belinda Chan Kwok Cheong ◽  
Cristian Contescu ◽  
Xavier Espinal Curull ◽  
Jan Iven ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Distributed Storage ◽  
Storage System ◽  
Primary Data ◽  
Disk Storage ◽  
The Road ◽  
Ongoing Work ◽  
Software Distribution ◽  
Microsoft Office

The CERN IT Storage group operates multiple distributed storage systems and is responsible for the support of the infrastructure to accommodate all CERN storage requirements, from the physics data generated by LHC and non-LHC experiments to the personnel users' files. EOS is now the key component of the CERN Storage strategy. It allows to operate at high incoming throughput for experiment data-taking while running concurrent complex production work-loads. This high-performance distributed storage provides now more than 250PB of raw disks and it is the key component behind the success of CERNBox, the CERN cloud synchronisation service which allows syncing and sharing files on all major mobile and desktop platforms to provide offline availability to any data stored in the EOS infrastructure. CERNBox recorded an exponential growth in the last couple of year in terms of files and data stored thanks to its increasing popularity inside CERN users community and thanks to its integration with a multitude of other CERN services (Batch, SWAN, Microsoft Office). In parallel CASTOR is being simplified and transitioning from an HSM into an archival system, focusing mainly in the long-term data recording of the primary data from the detectors, preparing the road to the next-generation tape archival system, CTA. The storage services at CERN cover as well the needs of the rest of our community: Ceph as data back-end for the CERN OpenStack infrastructure, NFS services and S3 functionality; AFS for legacy home directory filesystem services and its ongoing phase-out and CVMFS for software distribution. In this paper we will summarise our experience in supporting all our distributed storage system and the ongoing work in evolving our infrastructure, testing very-dense storage building block (nodes with more than 1PB of raw space) for the challenges waiting ahead.

Software Testing Strategy

2014 ◽  
Vol 6 (2) ◽  
pp. 23-36
Author(s):  
Fatma Molu
Keyword(s):  
Life Cycle ◽  
Large Scale ◽  
Critical Role ◽  
Real Life ◽  
Banking System ◽  
System Transformation ◽  
Financial Systems ◽  
Project Completion ◽  
Basic Features ◽  
Project Life

Complex financial conversion projects with large budgets have many different challenges. For companies that want to survive in conditions of tough competition, legacy (old) systems must continue to provide the required service throughout the project life cycle and in some circumstances even after project completion partly. In this case, the term coexistence comes into prominence. During this period, testing phase takes more critical role while integration systems' complexity and risk amount increase. Determining testing approach to use is essential to make sure both transformed and legacy systems provide service synchronously. In this paper, testing practices applied in the long conversion processes are discussed. Primarily, the basic features of the critical financial systems are addressed and then the main adoption methods in the literature are summarized. Then a variety of testing methodologies are presented depending on those adoption methods. These samples based on real-life experiences of transformation project. The most extensive example of real-time online financial systems is core banking systems. This paper covers the testing life cycle process of the large scale project of core banking system transformation project of a bank in Turkey.

scholarly journals Medical Records: a framework for establishing a record system.

BMJ ◽  
1981 ◽  
Vol 283 (6295) ◽  
pp. 833-834
Author(s):  
L I Zander
Keyword(s):  
Medical Records ◽  
Record System
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